Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions. [PDF]
Wang J +5 more
europepmc +1 more source
The Spatiotemporal Genetic Architecture of Seed Vigor in Upland Cotton
Leveraging the semi‐automated SeedRanger platform, we profiled the germination kinetics of 356 cotton accessions at a 30‐min interval. This high‐throughput phenomic approach delineated a temporal genetic network comprising 541 stage‐specific loci. Crucially, functional validation identified FLA2 as a pivotal, auxin‐modulated regulator that orchestrates
Luyao Wang +32 more
wiley +1 more source
Mitigating catastrophic forgetting in lifelong learning: a hybrid architecture integrating neural ordinary differential equations with memory-augmented transformers. [PDF]
Zhou S, Li Q.
europepmc +1 more source
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley +1 more source
Composite B-spline regularized delta functions for the immersed boundary method: Divergence-free interpolation and gradient-preserving force spreading. [PDF]
Gruninger C, Griffith BE.
europepmc +1 more source
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
Mathematical Modeling of Population Dynamics of Pollinators: A Survey. [PDF]
Huancas F +3 more
europepmc +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Wearable‐derived diurnal alignment between physical activity and device temperature, decomposed into 24 h coupling strength (M24), phase deviation (D24), and 12 h harmonic magnitude (M12), is examined in approximately 90,000 UK Biobank participants.
Han Chen +6 more
wiley +1 more source
A New Definition of Peridynamic Damage for Thermo-Mechanical Fracture in Brittle Materials. [PDF]
Tao S, Han F.
europepmc +1 more source

